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Online Narrative Guides For Illuminating Tissue Atlas Data And Digital Pathology Images

Rumana Rashid, Yu-An Chen, John Hoffer, Jeremy L. Muhlich, Jia-Ren Lin, Robert Krueger, Hanspeter Pfister, Richard Mitchell, Sandro Santagata, Peter K. Sorger

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ABSTRACTThe recent development of highly multiplexed tissue imaging promises to substantially accelerate research into basic biology and human disease. Concurrently, histopathology in a clinical setting is undergoing a rapid transition to digital methods. Online tissue atlases involving highly multiplexed images of research and clinical specimens will soon join genomics as a systematic source of information on the molecular basis of disease and therapeutic response. However, even with recent advances in machine learning, experience with anatomic pathology shows that there is no immediate substitute for expert visual review, annotation, and description of tissue images. In this perspective we review the ecosystem of software available for analysis of tissue images and identify a need for interactive guides or “digital docents” that allow experts to help make complex images intelligible. We illustrate this idea using Minerva software and discuss how interactive image guides are being integrated into multi-omic browsers for effective dissemination of atlas data.